chaf1a Antibody

What is CHAF1A and why is it significant in research?

CHAF1A is the largest subunit (p150) of the Chromatin Assembly Factor 1 (CAF-1) complex, which is the only histone chaperone known to assemble histones H3 and H4 onto newly synthesized DNA both in vitro and in vivo . This 938 amino acid multidomain protein plays crucial roles in nucleosome assembly, chromatin silencing, heterochromatin integrity, and DNA replication . It has emerged as an important research target due to its implications in cancer progression, cell cycle regulation, and response to immunotherapy .

What are the key specifications when selecting a CHAF1A antibody?

When selecting a CHAF1A antibody, researchers should consider:

• Reactivity: Confirm species reactivity matches your experimental model (commonly human and mouse)

• Applications: Verify validation for your specific application (WB, IP, IF, IHC, ChIP)

• Specificity: Review validation data showing specific detection at the expected molecular weight (~150 kDa)

• Clone type: Consider whether polyclonal or monoclonal is appropriate for your application

• Immunogen region: Check if the epitope is in a region of interest for your study

How should CHAF1A antibody validation be performed for new cell lines or tissues?

Thorough validation should include:

• Western blot: Confirm single band at expected molecular weight (~150 kDa)

• Positive controls: Include validated cell lines such as Jurkat or HeLa cells

• Knockdown validation: Include CHAF1A shRNA/siRNA samples as negative controls

• Cross-reactivity assessment: Test on multiple species if cross-species applications are planned

• Peptide competition: Perform blocking experiments with immunogenic peptide to confirm specificity

• Dilution optimization: Perform titration series to determine optimal antibody concentration for your specific samples

What are the recommended protocols for CHAF1A detection by immunohistochemistry?

For optimal CHAF1A detection in tissue sections:

• Fixation and embedding: Standard FFPE processing is suitable

• Antigen retrieval: Use TE buffer pH 9.0 (preferred) or citrate buffer pH 6.0

• Antibody dilution: Start with 1:20-1:200 dilution and optimize based on signal intensity

• Detection system: Polymer-based detection systems provide optimal sensitivity

• Positive control selection: Include cervical cancer tissue samples as positive controls

• Scoring methodology: Consider using H-score system for semi-quantitative assessment of nuclear staining intensity

Nuclear localization of CHAF1A is expected, with higher staining intensity often observed in cancer tissues compared to adjacent normal tissues .

What is the optimal procedure for CHAF1A immunoprecipitation experiments?

For successful CHAF1A immunoprecipitation:

• Cell lysis: Use RIPA buffer supplemented with protease inhibitors

• Antibody amount: Use 0.5-4.0 μg antibody per 1.0-3.0 mg of total protein lysate

• Pre-clearing: Pre-clear lysates with protein A/G beads to reduce background

• Incubation conditions: Incubate antibody-lysate mixture overnight at 4°C with gentle rotation

• Washing stringency: Perform at least 4-5 washes with TBS containing 0.1% Tween-20

• Elution method: Elute with 2X SDS sample buffer at 95°C for 5 minutes

• Controls: Include IgG control and input samples for accurate interpretation

Jurkat cells have been validated for successful CHAF1A immunoprecipitation experiments .

How can CHAF1A knockdown be efficiently achieved in experimental models?

Based on published research, effective CHAF1A knockdown can be achieved through:

• Lentiviral shRNA delivery: Using validated sequences like 5′-CCGGCCGACTCAATTCCTGTGTAAATTCAAGAGATTTACACAGGAATTGAGTCGGTTTTTG-3′

• Transfection method: Lipofectamine 2000 has been successfully used for delivery in 293T packaging cells

• Verification: Confirm knockdown efficiency by qRT-PCR (target >80% reduction) and western blot

• Cell line considerations: H1299, MDA-MB-231, and other cancer cell lines have shown successful knockdown

• Functional validation: Assess cell proliferation, colony formation, and cell cycle distribution to confirm functional effects

Knockdown efficiency of 84.7±1.2% has been reported using lentiviral shRNA delivery in H1299 cells .

How does CHAF1A knockdown affect the epigenetic landscape in functional studies?

CHAF1A depletion induces significant epigenetic alterations:

• Suppressive marks: Significant decreases in H3K9me3, H4K20me3, and DNA methylation (CpG)

• Active marks: Increases in H3K4me3, H3K36me2, and acetyl-lysine marks

• Chromatin accessibility: Higher chromatin accessibility as measured by ATAC-seq

• Recruitment patterns: Disruption of suppressive epigenetic protein complexes

• Gene expression: Reactivation of silenced genes, particularly relevant in viral latency models

These epigenetic changes explain mechanistically how CHAF1A functions as a transcriptional regulator, with implications for therapeutic targeting in cancer and viral latency models.

What is the relationship between CHAF1A expression and immune checkpoint inhibitor efficacy?

Recent research has revealed unexpected connections between CHAF1A and immunotherapy:

• Biomarker potential: High CHAF1A expression is associated with favorable response to immune checkpoint inhibitors in gastric cancer, despite being an oncogene

• Correlation with established markers: CHAF1A expression is positively correlated with microsatellite instability (MSI), tumor mutation burden (TMB), tumor neoantigen burden (TNB), and PD-L1 expression

• Immune cell infiltration: Associated with increased live infiltration of immune cells, particularly NK cells and M1 macrophages

• Mechanistic pathway: Potential inhibition of TGF-β signaling, a key driver of immune inhibition

• In vivo findings: CHAF1A knockdown alone inhibits tumor growth but impairs anti-PD-1 antibody efficacy

This paradoxical finding suggests CHAF1A may serve as an independent biomarker for immunotherapy response prediction beyond traditional markers like PD-L1, MSI, and TMB.

How does CHAF1A contribute to cancer cell resistance to genotoxic stress?

CHAF1A has been identified as a regulator of the translesion DNA synthesis (TLS) pathway:

• PCNA interaction: CHAF1A enhances the interaction between PCNA and E3 ubiquitin ligase RAD18

• PCNA monoubiquitination: Promotes this critical modification for TLS activation

• Polymerase recruitment: Enhances recruitment of Y-family DNA polymerase Pol η

• Fork restart: Facilitates replication fork restart under DNA replication stress

• Genome integrity: Maintains genome integrity during replication stress

• Mechanism independence: This function is independent of CHAF1A's canonical role in histone assembly

This newly discovered function may explain why high CHAF1A expression is associated with poor prognosis in multiple cancer types and suggests potential therapeutic strategies for sensitizing cancer cells to genotoxic therapies.

How should researchers design chromatin immunoprecipitation (ChIP) experiments for CHAF1A?

For effective ChIP analysis of CHAF1A binding:

• Crosslinking conditions: Standard 1% formaldehyde for 10 minutes at room temperature

• Sonication parameters: Optimize to achieve DNA fragments of 200-500 bp

• Antibody amount: 2-5 μg of ChIP-validated CHAF1A antibody per immunoprecipitation

• Positive control regions: Include known CHAF1A-binding sites such as HIV-1 LTR Nuc-1 assembly sites

• Negative control regions: Include regions not expected to bind CHAF1A

• Validation approach: Confirm enrichment of associated epigenetic marks (H3K9me3, H4K20me3) at CHAF1A-binding sites

• Data analysis: Calculate fold enrichment over input and IgG controls

ChIP-seq analysis has demonstrated CHAF1A enrichment at specific genomic regions, particularly those related to heterochromatin and gene silencing.

What are the key considerations for multiplexed imaging of CHAF1A with other chromatin factors?

For effective multiplexed imaging:

• Antibody compatibility: Select CHAF1A antibodies raised in different host species than other target antibodies

• Sequential staining: Consider sequential rather than simultaneous staining when using same-species antibodies

• Fixation method: Paraformaldehyde fixation (4%) is suitable for preserving nuclear architecture

• Nuclear counterstain: DAPI works effectively as a nuclear counterstain with CHAF1A visualization

• Co-localization analysis: Use appropriate software (ImageJ, CellProfiler) for quantitative co-localization analysis

• Controls: Include appropriate minus-primary controls for each antibody

CHAF1A has been successfully visualized in multiplexed imaging approaches, particularly in studies examining nuclear condensate formation and co-localization with other chromatin modifiers.

How should researchers interpret divergent results between mRNA and protein expression of CHAF1A?

When facing discrepancies:

• Post-transcriptional regulation: Consider microRNA-mediated regulation or RNA stability factors

• Protein stability: Assess proteasome-dependent degradation mechanisms

• Antibody epitope accessibility: Different antibodies may detect distinct conformational states or protein complexes

• Subcellular localization: Confirm localization patterns as protein may redistribute without changing total levels

• Methodology validation: Cross-validate using multiple antibodies and detection methods

• Tissue heterogeneity: Consider that bulk analysis may mask cell type-specific differences

• Functional validation: Focus on functional readouts (e.g., knockdown effects) to resolve discrepancies

Both mRNA and protein expression analyses have shown utility in predicting CHAF1A's clinical significance, but protein-level analysis may provide more direct functional insights .

How does CHAF1A expression correlate with cancer progression and patient outcomes?

Meta-analysis of multiple studies shows:

• Expression patterns: Overexpression observed in 20 different cancer types compared to normal tissues

• Prognostic significance: High expression associated with poor prognosis in breast cancer, NSCLC, and other cancers

• Subtype associations: Higher expression in triple-negative breast cancer compared to luminal or HER2+ subtypes

• Genetic correlation: Association with TP53 mutations in breast cancer

• Metastasis and recurrence: Positive correlation with metastasis and recurrence in NSCLC

What molecular mechanisms underlie CHAF1A's role in cancer progression?

CHAF1A contributes to cancer through multiple mechanisms:

• Cell cycle regulation: Knockdown increases cells in S-phase while decreasing G0/G1 and G2/M phases

• Cell cycle proteins: Decreases expression of cyclin D1, CDK2, and SKP2 while increasing p21 and p27

• Metabolic reprogramming: Influences amino acid metabolism and energy metabolism pathways

• DNA damage response: Promotes translesion DNA synthesis pathway and fork restart after replication stress

• Immune modulation: Associated with immunosuppressive microenvironment in some contexts

• Epigenetic regulation: Maintains repressive chromatin marks that silence tumor suppressor genes

This multifaceted role makes CHAF1A a potential therapeutic target in cancer through direct inhibition or as a biomarker for treatment selection.

How can researchers harmonize apparently contradictory findings on CHAF1A's role in immunotherapy?

To resolve paradoxical findings:

• Tumor type specificity: Acknowledge that CHAF1A may have different roles across cancer types

• Dual functionality: Recognize that oncogenes can simultaneously promote tumor growth and immunogenicity

• Temporal considerations: Consider that CHAF1A's effects may differ during cancer initiation versus established tumors

• Biomarker integration: Combine CHAF1A with other biomarkers for improved predictive power

• Mechanistic dissection: Focus on the relationship between CHAF1A and TGF-β signaling

• Experimental design: Design experiments that can test both tumor-intrinsic and immune-modulatory functions

Studies have demonstrated that while CHAF1A knockdown inhibits tumor growth, it paradoxically impairs anti-PD-1 efficacy, potentially through activation of TGF-β signaling , suggesting context-dependent functions.